Impact analysis for distributed event-based systems

D. Popescu, Joshua Garcia, K. Bierhoff, N. Medvidović
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引用次数: 24

Abstract

Distributed event-based (DEB) systems contain highly-decoupled components that interact by exchanging messages via implicit invocation, thus allowing flexible system composition and adaptation. At the same time, these inherently desirable properties render a DEB system more difficult to understand and evolve since, in the absence of explicit dependency information, an engineer has to assume that any component in the system may potentially interact with, and thus depend on, any other component. Software analysis techniques that have been used successfully in traditional, explicit invocation-based systems are of little use in this domain. In order to aid the understandability of, and assess the impact of changes in, DEB systems, we propose Helios, a technique that combines component-level (1) control-flow and (2) state-based dependency analysis with system-level (3) structural analysis to produce a complete and accurate message dependence graph for a system. We have applied Helios to applications constructed on top of four different message-oriented middleware platforms. We summarize the results of several such applications. We demonstrate that Helios enables effective impact analysis and quantify its improvements over existing alternatives.
分布式事件系统的影响分析
基于事件的分布式(DEB)系统包含高度解耦的组件,这些组件通过隐式调用交换消息进行交互,从而允许灵活的系统组合和自适应。同时,这些固有的理想属性使DEB系统更加难以理解和发展,因为在缺乏显式依赖信息的情况下,工程师必须假设系统中的任何组件可能潜在地与任何其他组件交互,并因此依赖于任何其他组件。在传统的基于显式调用的系统中成功使用的软件分析技术在这个领域几乎没有用处。为了帮助理解和评估变更对DEB系统的影响,我们提出了Helios,这是一种将组件级(1)控制流和(2)基于状态的依赖分析与系统级(3)结构分析相结合的技术,可以为系统生成完整而准确的消息依赖图。我们已经将Helios应用于构建在四个不同的面向消息的中间件平台之上的应用程序。我们总结了几个此类应用的结果。我们证明Helios能够有效地进行影响分析,并量化其对现有替代方案的改进。
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